Page 28 - Ai Robogenius

This way, it can find hidden patterns or trends without anyone telling it exactly what to do. This
approach is useful because sometimes it’s hard to write clear rules for complicated or messy
data. The machine’s ability to discover patterns helps solve problems that rule-based systems

cannot handle easily.
Let us understand the concept of a learning-based AI approach using a simple example
of fruit images. In this method, the AI model is given unlabelled data—in this case, various

fruits like apples, bananas, grapes and pears—without any names or predefined categories.
The machine does not know what each fruit is called or how it should be grouped. Instead of
following fixed rules, the AI analyses the visual features of the fruits such as shape, colour and

size to find patterns. It then learns from these patterns and clusters similar items together.
For example, it groups all bananas together based on their long, curved shape and yellow colour
and clusters apples together based on their round shape, even if the colours vary. This process
is known as unsupervised learning, where the machine identifies categories or groups by itself
without human-provided labels.

The following image effectively demonstrates how a learning-based AI model can independently

observe, analyse and group data based on the features it detects.

Learning Approach

Unlabelled Data

Model
Used to Train Dataset

Unlabelled Data Output

Output is clustered based on patterns observed by the machine:
Left is based on roller stakes, Middle is based on Ice Skates and Right is based on Inline skates.

Task Century #Creativity
21 st
Skills #Technology Literacy
Case: Substantial Electricity Bill (Continued…)

You begin designing a sensor and alarm system that detects movement in the room. If there is
no movement, the alarm will sound to remind someone to turn off the lights and fans.

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